Human Resources Has a Data Problem. Here’s How To Fix It

According to a survey of human resources professionals, 59% of respondents said they  felt their departments were undervalued by the employees they serve. The survey organizers concluded the root cause of the issue was “HR [having] a PR problem.” But I think the problem is much bigger than that. The real issue is that HR departments have a data problem.

Recently, I heard someone say, “What isn’t measured doesn’t matter.” HR departments have often had difficulty demonstrating value to organizational leadership. While things have improved from the days when some HR departments had difficulty answering a question as simple as how many employees work here at the organization, they can still miss the mark in measuring what matters.

For example, after reviewing several HR department annual reports, I found that often the data and statistics reported focused on outputs rather than outcomes. For example, one government HR department report included the composition of the organization’s workforce, i.e., number of employees, age category, years of service, racial/ethnic group and recruiting events attended; job vacancies posted; new hires; resignations and retirements; and training sessions offered and employees who attended.

While it’s good that HR can detail what it is doing and has systems that can produce data like these, this is an example of what I refer to as counting but not measuring.

Counting outputs is different from measuring outcomes. HR’s fundamental mission is to enable the organization to attract, develop, engage and retain talent, as effectively and efficiently as possible. HR needs to measure whether it is succeeding in this mission, by going beyond describing activities and evolving to counting outputs. In other words, it needs to measure if HR activities are making a difference.

Measuring outcomes is harder than counting outputs—but it’s more important than ever in the intense competition for talent in our post-pandemic workplace.

So what should HR measure? Below are some examples of how I believe HR can evolve from counting outputs to measuring outcomes.

Training

Counting the number of training courses or attendees can be useful, but the real question is whether training is improving employee competencies and organizational performance. And if not, why? These are the outcomes that can enable the organization to decide how to best allocate scarce training resources.

Recruiting and Hiring

It’s not just about the number of recruiting events, applicants and hires. It’s not even about time to hire, although government hiring must be faster and more user-friendly or it will continue to lose out on the best candidates.  Instead, outcomes that matter are whether the organization is accessing the most productive recruiting sources, and whether the best talent is being hired, excelling and staying.

If data reveal that the answer to any of these questions is no, then the organization needs to understand why—and fix what isn’t working. Here are a few examples of metrics to assess recruiting and hiring outcomes:

·  Percent of job offers accepted

·  Diversity of hires

·  Candidate evaluations of their hiring experiences (both from those who were hired and those who weren’t)

·  Return on investment from various recruiting sources, i.e. what sources deliver the highest yields

·  Cost per hire

·  Hiring managers’ satisfaction with the quality of candidates and hires

·  Turnover among new hires, including by gender, race/ethnicity, work unit and manager

·  Reasons for new hire attrition, i.e. exit interview data

·  New hires’ evaluations of their onboarding experiences

·  Performance of new hires, as assessed by performance evaluations and supervisors

Employee Turnover

Turnover percentage is another common metric that may not always reveal much. I've been asked what a “good” turnover rate is. That depends mostly on who is leaving and why. Is the organization losing its best performers, recent hires, employees in mission-critical jobs or in disproportionate members of certain work units or demographic groups?

What may appear to be low turnover can mask real retention issues that need to be addressed.

For example, if turnover is high among new hires, the organization may need to look at its hiring and onboarding processes. If there are turnover disparities in mission-critical jobs, work units or specific demographic groups, then the organization needs to ask what are the root causes of any alarming gaps, what can the organization do to minimize “bad” turnover, And how can the organization use turnover data to predict—and perhaps minimize—future turnover.

In other words, drill down on the overall turnover numbers to understand where the organization needs to act to minimize bad turnover.

Employee Engagement

Decades of research have revealed that a high level of engagement drives organizational performance. “Quiet quitting” is just another way of describing low engagement. Just like other key factors, engagement needs to be measured, ideally through regular employee surveys.

Unfortunately, not enough government organizations are doing this. The MissionSquare Research report, “State and Local Workforce 2022,” revealed that while 96% of HR leaders identified engagement as an important issue, only 39% conducted employee surveys to measure it. This is a big data gap.

Too often organizations try to build engagement with social activities. As I wrote in my book Engaging Government Employees, “free pizza and Coke on a Friday afternoon isn’t an engagement strategy.” 

Engagement needs to be measured, including empirically identifying what influences engagement so the organization can focus on those drivers.

Overtime

Employee overtime is an important and emerging area of inquiry and analysis. Many government organizations are collecting and analyzing overtime data to see if any employees are in danger of fatigue that can lead to dangerous errors and injuries, slow reaction time, and reduced alertness. Employee fatigue, especially in 24/7 operations, is estimated to cost the U.S. economy $400 billion annually.

So why don’t organizations measure instead of count? Three reasons: 1)They lack the statistical and analytical expertise to collect, analyze and interpret data. 2) Different reporting systems across the organization can make it difficult to aggregate and compare data. 3) Organizations may not have high-quality and comprehensive software that can collect and analyze the data. 

Some of you may remember the outspoken, irrepressible and often controversial Ed Koch, the former mayor of New York City who went on to arguably greater fame as the [ judge on The People's Court. As mayor, his catch phrase was “How’m I doin’?” which he habitually asked anyone he encountered on the streets of the city. That was a good question then and it’s a good question now. Answering this question by measuring outcomes will demonstrate HR’s value and enhance its stature in any organization.